Foundations and Trends in Machine Learning丛书

2016/3/5: 更新至Volume 8, Issue 5-6，附带其他福利 http://pan.baidu.com/s/1eReaDz0
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Michael Jordan主编的，很好的一套书，每本都是machine learning前沿课题的一个综述。
这是官网链接，要下载的话点这里点这里~~
还没有一本一本研究过，先丢一个合集的下载吧，截至到最新的Volume 5, Issue 2-3。其中Volume 2, Issue 2这本没有正式版，在这里求一下。
以下是书目。
Volume 5, Issue 2-3
Determinantal Point Processes for Machine Learning
By Alex Kulesza (University of Michigan, USA) and Ben Taskar (University of Pennsylvania, USA)
Volume 5, Issue 1
Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems
By Sébastien Bubeck (Princeton University, USA) and Nicolò Cesa-Bianchi (Universita degli Studi di Milano, Italy)
Volume 4, Issue 4
An Introduction to Conditional Random Fields
By Charles Sutton (University of Edinburgh, UK) and Andrew McCallum (University of Massachusetts, Amherst, USA)
Volume 4, Issue 3
Kernels for Vector-Valued Functions: A Review
By Mauricio A. Álvarez (Universidad Tecnológica de Pereira, Columbia), Lorenzo Rosasco (Istituto Italiano di Tecnologia, Italy and MIT, USA) and Neil D. Lawrence (University of Sheffield and The Sheffield Institute for Translational Neuroscience, UK)
Volume 4, Issue 2
Online Learning and Online Convex Optimization
By Shai Shalev-Shwartz (The Hebrew University of Jerusalem, Israel)
Volume 4, Issue 1
Optimization with Sparsity-Inducing Penalties
By Francis Bach (INRIA, Paris, France), Rodolphe Jenatton (INRIA, Paris, France), Julien Mairal (University of California, Berkeley, USA) and Guillaume Obozinski (INRIA, Paris, France)
Volume 3, Issue 3-4
On the Concentration Properties of Interacting Particle Processes
By Pierre Del Moral (INRIA, Universite Bordeaux 1, France), Peng Hu (INRIA, Universite Bordeaux 1, France) and Liming Wu (Institute of Applied Mathematics, AMSS, Chinese Academy of Sciences and Universite Blaise Pascal, France)
Volume 3, Issue 2
Randomized Algorithms for Matrices and Data
By Michael W. Mahoney (Stanford University)
Volume 3, Issue 1
Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
By Stephen Boyd (Stanford University), Neal Parikh (Stanford University), Eric Chu (Stanford University), Borja Peleato (Stanford University) and Jonathan Eckstein (Rutgers University)
Volume 2, Issue 4
Dimension Reduction: A Guided Tour
By Christopher J.C. Burges (Microsoft Research)
Volume 2, Issue 3
Clustering Stability: An Overview
By Ulrike von Luxburg (Max Planck Institute for Biological Cybernetics)
Volume 2, Issue 2
A Survey of Statistical Network Models
By Anna Goldenberg (University of Toronto), Alice X. Zheng (Microsoft Research), Stephen E. Fienberg (Carnegie Mellon University) and Edoardo M. Airoldi (Harvard University)
Volume 2, Issue 1
Learning Deep Architectures for AI
By Yoshua Bengio (Universite de Montreal)
Volume 1, Issue 4
Learning Representation and Control in Markov Decision Processes: New Frontiers
By Sridhar Mahadevan (U. Mass, Amherst)
Volume 1, Issue 3
Property Testing: A Learning Theory Perspective
By Dana Ron (Tel-Aviv University)
Volume 1, Issue 1-2
Graphical Models, Exponential Families, and Variational Methods